System and method for modeling, fuzzy concept mapping, crowd sourced supervision, ensembling, and technology prediction

ABSTRACT

The invention provides a system and method for providing ttx-based categorization services and a categorized commonplace of shared information. Currency of the contents is improved by a process called conjuring/concretizing wherein users&#39; thoughts are rapidly infused into the Map from user entry or movement of ttxs; or pre-entry of fxxts of text, transform relationships, associations among ttxs, commonalities, or ttxs. A Map is generated based upon use of selected sets of relationships between ttxs, allowing for construction of subjective, compartmentalized, or objective depictions and organizations. The Map provides for modeling where ttx nodes are objects. The Map ttxs also serve as binding points to other modeling paradigms similar to how equations are bound to spreadsheet cells, but using the extended information of a graph rather than a rectangle of cells. As a new idea is sought, a goal is created for a search. After the goal idea is found, a ttx is concretized and categorized. The needs met by such a Map are prior art searching, competitive environmental scanning, competitive analysis study repository management and reuse, innovation gap analysis indication, novelty checking, technology value prediction, investment area indication and planning, and product technology comparison and feature planning.

This application references and is derived from provisional patent application numbered Ser. No. 61/694,259 with EFS ID of 13611226, and this application claims priority from that provisional application. This application is a continuation from non-provisional patent application numbered Ser. No. 14/014,229, wholly included herein by reference. This specification is not intended to contain any new matter from the initial application, but does disclose helpful explanations. Note that this is a continuation application. While there are updated terms of art introduced into this amendment due to changes in the science, there are no changes in scope in the specification of this amendment. The original specification addressed syntactically suggested associations representing relationships stemming from syntax transforms (here known as a syntax deconstruction or interpretation rule or heuristic). These were not addressed by claims in that application, but the scope was succinctly stated prescribing the use of transformational grammar techniques as the method of syntactically suggested associations population and how such information from document scraping and ingesting is used for imputing information. For clarity, the latter function is signaled by the same phrase “represent relationships based upon a syntax deconstruction or interpretation rule or heuristic” in the Definitions section of the non-provisional patent application numbered Ser. No. 14/014,229.

FIELD OF INVENTION

The invention relates generally to the field of information technology. More specifically, but not by way of limitation, the invention relates to a system and method for concept-based management of categorizations or classifications to organize a commonplace, enhancing the navigability of very large information bases by providing in-depth sub-categorization of terminology bases, providing users with incentives to be creative, protecting crowd sourced contributions, managing searches for what is known either within, or in some accessible location outside of it, and establishing communities associated especially with the concepts, or its narrow categories, and particularly in Intellectual Property. It provides a user a searching tool for something known or unknown, capturing the concept if unknown to be reused as if known. This invention extends to new forms of fuzzy clustering and hierarchical self-organizing maps.

BACKGROUND

Today, in fields ranging from the general use of conceptual diagraming to specific purposes such as prior art searching, competitive environmental scanning, competitive analysis study repository management and reuse, innovation gap analysis identification, novelty checking, technology prediction, investment identification and planning, and product technology comparison and feature planning, users are ever more in need of finding very specific and highly relevant information from a mass of data that is not organized.

Known systems for ideation and innovation, developed over centuries, are closed so that the ideas generated are hidden for long periods. While this is somewhat effective in a commercial sense, the attitude fostered and results are often counter-productive for society. Modern concepts of open software and crowd sourcing, coming from the utopian view, also have faults.

SUMMARY OF THE INVENTION

The invention provides, in one embodiment, a system and method for providing crowd sourced consensus building, topic categorization services, a commonplace, and on-line community services by topics.

A result of the system and method is a Common Mental Map (CMM) for navigation. A visualization of a map provides a customized view of this ‘best available’ information, with objective and subjective views as information from users and disparate external sources is merged.

A user searching for something, known or unknown, provides one source of information for the commonplace. By capturing the concept searched for, the system saves the creative thought for reuse, and captures the fact of the search for that concept for value prediction.

The commonplace provides for analysis and prediction on a ‘best available’ data basis.

The term concept is too general to be used in the following. Generally, concepts are ttxs represented by cnxpts. The Topic Map Standard ‘subject’ is similar to the ttx, and the ‘topic’ is similar to the cnxpt, but more general.

The following outlines a search and categorization tool useful, in one embodiment, for rapidly finding tcepts, TPLs, or appcepts stored in a CMMDB that contains a structured list of categories including, but not limited to: fields of study, categories of tcepts, and categories of appcepts.

In one embodiment, the categorization is visualized, in one CMMV visualization technique called a map, as a visible ‘skin’ of a sphere that represents, including, but not limited to, a: cnxpt, goal, tcept, tcept category, TPL, tplxpt, appcept, appcept category. The CMMV ‘category’ spheres may contain internal spheres that represent, including, but not limited to, a: tcept, tcept category, appcept, appcept category, or another ttx. The CMMV ‘category’ structure is derived from various relationships in the CMMDB. The CMMDB is initially populated by automated consolidation of existing indices and tools such as cluster and cross-citation analysis, but is maintained and extended by crowd source collaboration, the ease of which is improved by effective visualization and editing interfaces. ‘Votes’ on the existence, validity, relationships, categorization, relevance of external information, and data quality of info-items within the CMMDB are the basis for reaching consensus on the accuracy of the categorization, prediction, naming, and description.

This system is intended to contain the basis of categorization for, including, but not limited to, ttxs and tcepts. The tcepts are not only historic, but prospective.

Purposes

An embodiment of the invention provides management of a CMMDB in a specific domain of the owner's choice.

An embodiment of the invention provides a visualization tool for depicting a map of the ttxs in a CMMDB, allowing map navigation, searching, refinement operations, execution of analytics, and interaction with associated communities.

An embodiment of the invention provides the mechanisms and procedures to achieve a CMMDB that is the best available source for a list of ttxs.

An embodiment of the invention provides the mechanisms and procedures to achieve a CMMDB database that is the best available source for a list of txpts and appcepts.

An embodiment of the invention provides the mechanisms and procedures to utilize a combination of user discussions, categorizations from outside, collected concretizations of conjurings, and the prior state of the stored Common Mental Map to provide a base upon which to users can search for abstract thoughts that are converted to new categorized ttxs to provide a continually improved and explicit formal specification of the ttxs that are assumed to exist in some Area of Interest and the relationships that hold among them.

An embodiment of the invention provides a method and apparatus for providing ttx categorization visualizations (“maps”).

An embodiment of the invention provides a method and apparatus for managing the lifecycle of a ttx, comprising: receiving data indicating a ttx; categorizing the data indicating the ttx to associate the data with one of a predetermined plurality of categories or a new category; setting access controls for the ttx data, disseminating the ttx data to user computing systems for view and use; accepting extensions, improvements, and refinements of the ttx characteristics; accumulating user interest information; selling or licensing the ttx data.

An embodiment of the invention provides management of a crowd sourcing paradigm for ideation providing teasing out of new innovations into a global common ground to share information; confidentiality in handling of the new ideas; confidential comparison to similar ideas; empowering patent protection; establishing collaborative development; predicting fruition and value; and securitizing innovations, all while language issues are reduced or eliminated by utilizing language independent storage and visualization with a multi-dimensional structure of symbols and diagrams and filters providing for display of language specific information when available.

An embodiment of the invention provides the mechanisms and procedures to create and expand a CMMDB to a number of users in a ‘crowd sourcing’ construct to conceptualize, or to add, concretize, and refine information about: including but not limited to: tpxs, ttxs, tcepts, and appcepts.

An embodiment of the invention provides a method for providing ttx categorization by consensus clustering within a fxxt, comprising: receiving data indicating a ttx within a fxxt, the data including at least one of a defining of a search goal, a defining of a query, a marking of a place on a visualization derived from the CMMDB, an extension of a ttx, a subdividing of a ttx, a combining of two ttxs to form a convergence, a defining of a new ttx, a stating that a ttx is different from another ttx, a defining of a contradictory feature or requirement for an existing ttx, a coalescing of a ttx into the CMMDB, a stating that a ttx is defined by an information resource, a stating that an information resource is relevant to the definition of a ttx, a showing of interest in a ttx; calculating pairwise ttx identity indicator similarity values within a fxxt, the identity indicator similarities including at least one of a semantic distance between ttx textual definitions, a semantic distance between ttx descriptions, a semantic distance between ttx names, commonality of occurrence relationships between each ttx and a information resource or relevant entity, commonality of association references between each ttx and a third ttx, a consensus vote toward similarity of the ttx pair, a prior ranking of semantic similarity recognized as generally accurate, or some combination of these; iteratively forming cluster ttxs to indicate a grouping of similar ttxs by a pairwise clustering algorithm utilizing the identity indicator similarity values; and merging, bottom up, the cluster ttxs with pre-existing category ttxs that share the exact same set of member ttxs; converting the remaining cluster ttxs to category ttxs.

An embodiment of the invention provides a method for monetizing ttx categorizations, including: registering at least one ttx category; offering registered ttx categorizations for sale; licensing for use the ttx categorizations and information associated the ttx categorization, granting access and enabling the ttx categorizations to be used by a customer on their local system; selling licenses to access communities associated with registered ttxs, accepting private data to be associated with ttxs, selling private data associated with ttxs, accepting registrations of consortiums formed for collaborative development of ttxs, accepting and processing collaboration and investment transactions involving consortiums, accepting and processing investment transactions involving innovation investment pools.

An embodiment of the invention provides a method for at least one of creation of, naming, specifying a scopx for, listing, voting on, rejecting, linking information to, or describing relationships between the at least two info-items of a field of science; tcept category; tcept; appcept; inventor; patent; product; or roadblock stopping satisfaction of an appcept by a tcept.

An embodiment of the invention provides a method for improving a ttx, including: providing incentives for improving a ttx definition, description, or characteristics; providing a ttx definition system; providing a ttx description system; providing a ttx characteristic change system; and providing community access to the ttx definition system, the ttx description system and the ttx characteristic change system.

An embodiment of the invention provides a method for improving the CMMSYS, including: providing incentives for improving a tpx definition, description, or characteristics; providing an information package requirement description system for stating CMMSYS specifications; providing a tpx definition system; providing a tpx description system; providing a tpx characteristic change system; and providing administrative and developer community access to the information package requirement description system and CMMSYS specifications; tpx definition system, the tpx description system and the tpx characteristic change system.

An embodiment of the invention provides user procedures and a toolset for obtaining one of entertainment, education, personal gratification, esteem for participation in the communities based upon the CMMDB.

An embodiment of the invention provides a method and a toolset for calculating and mining ttx value data from the CMMDB.

An embodiment of the invention provides a method for sharing ttx-based information, including but not limited to: providing related descriptions, analysis articles, identifying at least one of a value, strategy, purpose, application, feature, requirement, roadblock, related to the ttx; sharing visualization experiences including but not limited to: tours taken, visualization viewpoints.

An embodiment of the invention provides a method for customer purchase of at least one of a DataSet, an access right, a registration right, a methodology, an analytic, a model, an execution of a methodology, an execution of an analytic, an execution of a model, a license, a subscription, a CMMSYS component; including: viewing a list of at least one of DataSet packages for a selected ttx element or category, other DataSet package, an access right, a registration right, a methodology, an analytic, a model, an execution, a license, a subscription, a CMMSYS component; and accepting a selecting for purchase at least one DataSet package from the list of DataSet packages.

An embodiment of the invention provides a system configured to manage a customer purchase process, including: an e-commerce catalog module configured to present to a buyer a list of at least one of: DataSet package, an access right, a registration right, a methodology, an analytic, a model, an execution of a methodology, an execution of an analytic, an execution of a model, a license, a subscription, a CMMSYS component, the e-commerce catalog module further configured to receive from a buyer a selection of the at least one of a DataSet package, an access right, a registration right, a methodology, an analytic, a model, an execution of a methodology, an execution of an analytic, an execution of a model, a license, a subscription, a CMMSYS component from the list; a license and access control module coupled to the e-commerce catalog module, the license and access control module configured to limit access to the system to authorized users; a distribution module coupled to the e-commerce catalog module, the distribution module configured to connect with a user system and to provision the user system as needed to install, configure, and grant access to the selected at least one of a DataSet package, an access right, a registration right, a methodology, an analytic, a model, an execution of a methodology, an execution of an analytic, an execution of a model, a license, a subscription, a CMMSYS component.

An embodiment of the invention provides a system configured to share ttx-based analysis, including: a library configured to contain descriptions of tools and application elements, including but not limited to: methodologies, analytics, and models; and a CMMSYS information package catalog linked to the library, the CMMSYS information package catalog containing categorizations for the available elements described in the ttx library and e-commerce functions to enable users to obtain access to the elements for use.

An embodiment of the invention provides a method for alerting in a categorization system, including: notification regarding a change of, including but not limited to: a tpx or its characteristics; a ttx or its characteristics, a specified result from an analytic, the presence of a new developer, provider, or investor.

An embodiment of the invention provides a system configured to provide categorization services to a customer, including: a distribution engine; CMMSYS local system components, and an interface to a customer system, the interface coupled to the distribution engine, the distribution engine configured to distribute, including but not limited to, CMMSYS framework components and CMMDB data sets, the CMMSYS local system components configured to operate on one of a mid-tier server or a workstation, the interface configured to collect data from the customer system, the mid-tier server configured to serve CMMDB data, to manage access, to store and aggregate the collected data, and to release collected data to the central CMMDB, and workstation configured to store and aggregate the collected data, and to release collected data to the mid-tier and central CMMDBs.

An embodiment of the invention provides a method for protecting against full or uncontrolled disclosure of the information held regarding a tpx or ttx, such that only authorized users may obtain controlled information related to the ttx, and the access may be cut off where a license is exceeded or authorization has been terminated.

An embodiment of the invention provides management of a set of communities that each are connected to a ttx of a CMMDB in a specific domain of the owner's choice.

An embodiment of the invention provides methods for initiating and adding community information connected with a ttx, including: facilities for narrow topic chats, blogs, advertisements by nature of transaction desired, discussion forums, meeting, conversation, online-discussion, conference, or other event information, tokens for use to gain access to meetings or other events or to obtain discounts, articles, search scripts, search retrieval results, navigation tours, bookmarks or links to other information, information, information available for purchase or subscription, surveys, contact lists, personal profiles, inventor/conjurer information, development consortium information, and access rights and management information for each of the community facilities.

An embodiment of the invention provides a method to at least one of become developer, become publisher, become customer, become member, advertise, offer, search for, sell, select, purchase, register, distribute, offer for download, request, opt-in for, offer access to, sell access to, grant access to, join, or publish the at least one of the new, enhanced, improved, corrected, or revised at least one of portal function, body of information, subscription, DataSet, or access right.

An embodiment of the invention provides a method to incentivize use by users by at least one of offering awards, membership in a community, access rights, right to own, right to advertise, information, on-line personality/presence, discounts, prizes, recognition as at least one of expert, being creative, added knowledge, provided editing, made significant leap in invention; inclusion by at least one of a developer; a contributor; a publisher; a member of a development consortium; a member of a special group of achievers.

An embodiment of the invention provides a system configured to distribute ttx categorizations in a network, the system including a framework, the framework configured to distribute CMMDB information packages and included tpx and ttx information with restricted use IDs, to configure and control access, and to collect tpx and ttx data, imports, and categorization data from the network.

An embodiment of the invention provides a method for registering a CMMSYS information package, including: registering as a user on a portal to the system; provisioning the CMMSYS information package; establishing access; connecting to a CMMDB; and accessing and collaboratively improving the CMMDB, portal tools enabling the user to access tpx and ttx information and to submit tpxs, ttxs, and descriptive information to the CMMDB, and tools enabling administrators and developers to improve the CMMSYS.

An embodiment of the invention provides a method for managing a CMMSYS information package lifecycle, including: stating a requirement for the package, developing the package, certifying the package, distributing the package during provisioning, licensing the use of the package, registering the package, configuring the package, authorizing the package for use, granting access to the package, providing access to the package, terminating access to the package, terminating the license for the package, terminating the registration for the package, reconfiguring the package, re-provisioning the package by update.

An embodiment of the invention provides a method for managing a consortium for collaborative ttx development, preparing and submitting patent applications, forming a business, accepting or offering investment, including but not limited to: providing a consortium member exchange; coordinating member to candidate communications for negotiations for joining the consortium, registering members into the collaborative, managing secure storage of consortium documentation and tracking contributions, coordinating member to investor communications for negotiations for funding the consortium, registering members into the collaborative, collecting and distributing investment funds, and providing a contribution submission tool.

An embodiment of the invention provides a method for managing a collaborative development process, including: providing a developer exchange Website; registering a developer on the exchange Website; and providing information package submission tools via the exchange Website.

An embodiment of the invention provides a system and method for managing the rapid application for patents suitable in a first to file patent system, consisting of: ideation; methodology based completion of the minimum necessary for patent application; online collaboration mechanism for assisted preparation of an application; preparation for electronic patent application; assistance for electronically filing the application; electronic application and payment mechanism and process; online auction mechanism and process for licensing and assignment of patent rights; online investment mechanism and process for funding invention and for funding development; online option investment mechanism and process for funding invention and for securing future patent rights; and online intellectual property portfolio management.

An embodiment of the invention provides a system and method for displaying for a user a categorization, graph, directed graph, precedence diagram, or graphical forest arranged in an esthetically acceptable manner for the user according to: their subjective opinion, their subjective opinion considering the opinions of others, the objective opinion as formed by a crowd, the consensus opinion of an ensemble of machine learning results, or the subjective opinion of the user considering the opinions of others as well as an ensemble of machine learning results.

Other Advantages

The features and advantages of the invention will become apparent from the following drawings and detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the invention are described with reference to the following drawings, wherein:

FIG. 1 is a block diagram of a system architecture, according to an embodiment of the invention;

FIG. 2 is a block diagram of a functional architecture, according to an embodiment of the invention;

FIG. 3 is a block diagram of the query and conjure process, according to an embodiment of the invention;

FIG. 4 is a workbench user interface view showing the visualizations and maps for navigation, according to an embodiment of the invention; and

FIG. 5 is a workbench user interface view showing culling views, according to an embodiment of the invention.

DETAILED DESCRIPTION

The invention is directed to an improved information creativity, collection, categorization, and retrieval lifecycle, a functional architecture (also described hereinafter as a framework), and improved methods for providing network-based creativity, ttx collection, categorization, retrieval, and exploitation. Embodiments of the invention provide general tools for creativity, categorizing, virtual mapping, visualization, search, and retrieval of ttxs and its extensions for web communities and analytics. Embodiments of the invention also provide a specialization of the general tools directed to technology innovation, creativity, and categorizations, as well as the procedures for manipulating categorizations and use of the tools, technical information categorization and retrieval controls, and business processes for incentivization and fee collection.

Sub-headings are used below for organizational convenience, but do not necessarily limit the disclosure of any particular feature to any particular section of this specification.

Observations: Advantages and Disadvantages

One use of creativity is in technology innovation. One use of creativity is in legal argument, resulting in development of law.

Creativity

There is a need to reuse the efforts of others over time. As an example, competitive strategists draw a breakdown diagram of the field they are studying, and summarize their research on the basis of the diagram, resulting in a paper based but reusable understanding of the relationships between technology application domains and players. There is a need is to make this structure available and efficient for users, so that understanding of the knowledge is progressive and the amount of work required of each individual user is small.

Legal Clarity

Google performs searching of prior art and legal issues with loosened constraints and poorer results for a wider market of topics, but none of these systems offer all that is needed by a researcher who must work effectively, retain and update his work effortlessly, combine the results needed from several sources, and spend less to get the satisfactory result sought. Legal analysis could be built on the shoulders of what others considered rather than merely on their results in court opinions. The strength of an argument could be predicted where prior success at use of a position could be measured, but it can also be predicted by an attorney considered and rejected its use, given a similar fact pattern.

Sharing of Creative Results

There is thus a need to move ideas from those who have them to those who can generate higher value from them. To do so, this need demands that the ideas have to be collected, managed, organized, made retrievable, made useful for valuation and analysis, and, set to be the anchoring point to which new material can be related in a cognitive structure.

Learning

Here, meaningful learning involves the assimilation of new ttxs and propositions into existing cognitive structures.

Information Management Tools

In the past, technology information categorization and retrieval meant prior art searching at the patent office, a competitive intelligence study, or a technology road mapping project at a product company. Each of these ad hoc exercises consistently result in one time reports that become stale rapidly. The infrastructure for the studies—the queries and intermediate results—are usually lost soon after the report is written, and have to be recreated when the inevitable need for a repeat of the effort occurs.

Another need is in environmental scanning within competitive intelligence. Management is driven to see farther out strategically and they often realize how ineffective their tools and organizations are when they are blind-sided by a competitor from another part of the world or another industry.

The rise of data mining and investment vehicles and products improves the market for new analytic and investment products.

Name and Relationship Based Information Management Tools

There is a need to provide deeper classification. Experts are held back when only superficial descriptions of ttxs are available, meant only for the novice. Novices need to start at a general level and progress toward detail only to the degree they must based upon their task. Experts need to be concerned about the future, while investors need to be concerned about the timing of invention, inventors need to know about the details of prior art, and competitive analysts need detailed information about very specific topics. Novices need little of these, but want to find out whether an idea they have considered may have been invented already to build on the shoulders of others.

There is a need to reduce redundancy and provide authority control. Among normal textual works, this problem is relatively small, but not so where the system is ideation centric.

There is a need to name ttx categories found in an automated categorization process. Human input is often the only possible method for correcting such naming to obtain unique names, and even so, it is sometimes unrealistic to expect that uniqueness is possible. There is a need for some ability to improve understandability and adherence to explicit or implicit naming conventions.

There is a need to edit relationships in databases. Databases with deep relationship chains, deep taxonomies, and ontologies are in greater use as more information objects are managed. Scraped document contents are harvested to improve or form new relationships and ttxs. Often, the objects involved in these chains are of interest by specific communities, and online communities centered on the object could be helpful to increase communication efficiency for the interest group. What is needed is a tool to mitigate the authority and quality issues related to naming and relationship complexity.

What is needed is a tool that is effective enough to provide answers, offer initial values, and also to become the tool for cleanup. Users not obtaining good results for their needs will not be willing to clean up their data or the data from others. The answers must be effective, while possibly imperfect, even where the data is ‘fuzzy’ and ttx meanings are poorly constructed. The tool must be helpful but not overbearing, providing assistance to reduce user burden and making mere suggestions for improvement rather than denying progress where, for example, a value such as a name is not entered. The cleanup should support, including but not limited to: fix errant data; complete entries; improve understandability; assign best names; clarify description to remove ambiguities; obtain translations; fix grammar; enforce adherence to civility in discussion; enforce adherence to naming conventions and use of authorities; or approve use of suggested synonyms, translations, and homonyms. For scraping, document categorization, and entry of values, transforms of natural language to ttxs, ttx properties, and relationships is necessary to add information to the database of the Commonplace even if a natural language document is simply being categorized into a document repository. Transforms to natural language is needed to provide effective answers, improve understandability, and to obtain translations. Improvement of understandability of answers requires producing to a user the sources of information used and the paths used to determine the particular answer chosen rather than another.

Categorization Services

Known categorization services provide slowly changing and superficial categorization indices. While technologies, led by the Internet, have increasingly allowed for the easy sharing of knowledge and valuable IP, the information for categorization has been lacking, causing wild attempts at ‘semantic web’ and other research.

In one respect, known methods for procuring categorization services and data provide little or no effective harmonization between new locally defined ttx categorizations and newly defined ttxs from the central data store or even with new locally defined ttx categorizations at another user location. Thus, it falls to the buyer of such services or data to ensure that the categorizations and object definitions in their local system are reconciled with those of a central standard or with other buyer's local systems.

In another example, known methods provide inadequate business models for traceability and version control over changes made in central data stores (vendor's or private) and local systems that might be managed by users and might contain data not privy to the categorization service vendor. Again, it falls to the user of such services to ensure that the data is valid and up-to-date.

Further, known systems for providing categorization information from a central data store are lacking. For instance, they may be configured to distribute categorization information, or collect categorization information (data related to the categorization services), but not both effectively. Moreover, where systems are configured to collect categorization information, they may only be configured to report the collected categorization information, without a capability to timely reconcile and publish the collected knowledge to assist others in categorization, even within the users own organization.

For example, known systems do not sufficiently provide a cost-effective way to update categorizations based on changing categorization information from other users. Also, known tools aimed at helping Intellectual Property owners manage their own property provide solutions that allow them to categorize their property with that of others, but the categorization structures fail to recognize the complexity of the need. The insufficient tools cannot effectively serve product departments more generally causing both unnecessary infringement and wasteful reinvention.

There is an additional need to extend deeper the level of categorization of technologies as new off-shoot technologies are conceived or found in natural language descriptions. Current approaches require the user to develop the queries and filters needed to establish the membership of a particular category below the categories provided or where information needed is classified in multiple categories as defined by the categorization vendor. This constrains the sharing of the knowledge and forces inefficiency.

What is needed is a system and a technique for managing the various categorizations in their various fxxts, enabling an architecture of participation around categorization.

What is needed is a more robust system and method for managing categorization services, including the improved creativity methods, business methods, functional architecture, and lifecycle management processes associated with such management.

What is also needed is an improved txo-based information categorization and retrieval management paradigm to deal with a multi-source environment with few standards, providing streamlined methods for incentivized creation of new knowledge; retrieval and inclusion of current knowledge; incentivized refinement of stored knowledge; efficient access, reuse, sharing, and distribution of the stored knowledge; and management of the studies that require all of these. The need is not for unassembled pieces but a working combination. This often involves ‘harmonization’ of topic indexes from various sources.

Search and Retrieval

Similar searches are often performed repetitively when the community as a whole is considered. Often the information sought has been lost due to poor cataloging or categorization when the search is first attempted, or has become stale due to passing of time.

Most available content is unstructured so that it is difficult to locate pertinent data. As the cost of access and disk space has decreased, the volume of information available has grown tremendously. Elementary search engines that simply create indexes of keywords are becoming increasingly ineffective in identifying relevant information. There is a growing need for more effective search systems.

Again, by way of example, the complexity and detail involved in Prior Art searching are well known, as is the issue of language, where legal speak is difficult or where patents may be obtained in other jurisdictions.

There is an additional need to provide a system for performing search and categorization for rapidly finding tcepts or appcepts. The categorization must be a stored data CMMDB that contains a structured list of fields of study, tcepts, and appcepts where the structure is provided by various relationships.

There is an additional need to provide content and categorization currency or the users will not find the tool useful over time. The content and categorization should be the ‘best available’ or it will be seen as stale.

An additional need is that the returned results must be managed for a user during the query process and as a record of the query for reference later. These ‘scan hits’ are cumulatively important but are also in need of refreshing and any ability to rerun the query and notify the user of new information would be important to a user.

Thus, for instance, while a categorization of documents might be completed on a user's subjective view as contained in a user database, they are likely not categorized on the basis of an objective viewpoint of an overall organization's members as contained in a commonplace. Also, a categorization of documents might be completed on the basis of a subjective viewpoint of a vendor organization's categorizers as contained in a proprietary categorization database, making it difficult to retrieve documents from a vendor in a categorization a user has developed or an organization has built up.

Even if the forgoing needs are addressed, there is an additional need to present the information in a way that users may be educated, may remember context, and may search associatively (by co-location). This need has often been served by map making. To provide the map showing topics in proximity by similarity, the retrieved information must be transformed to associations, ttxs, and ttx properties, then the retrieved information must be assigned one or more categories and a map must be created based upon a possibly different categorization defined by the user for the map. While the categorization may be n-ary and very deep, the user needs to be able to understand it, forcing a dimensionality reduction.

Prediction

There is an additional need to provide worthwhile assessments of value and importance of tcepts. The average accuracy of these assessments is a measure of collected intelligence. The difficulty is perhaps best illustrated by the frustration most people experience with committees and meetings where the result is rarely much better than the result if the different participants had tackled the problem individually.

Although committees are obviously important and useful, in practice it appears difficult for them to realize their full potential. They fail to organize and they disband rapidly. At the same time, they do yield what may be called the ‘best available’ information and predictions because of the consensus reached. Small groups and other outliers may and often do believe that they can do better than the public in general, and they are too often correct to be ignored.

There is an additional need to raise the collective intelligence by speeding the evaluations of opinions, and to increase the efficiency of sharing the alternatives.

There is a need to present technologies from varying points of view. As examples, technologies must be seen with their antecedents for prior art, with their contemporaries for competitive intelligence and product assessment, along side yet to be developed technologies for looking ahead, by ownership, by application, and by importance. The need for mapping by these fxxts is needed for associative searching, to communicate current reality, and to stir imagination.

There is an additional need to provide prediction management so that the estimates of users about when some tcept may become real, and what value the reality will have can be stored, assessed, reconsidered, and totaled to obtain the ‘best available’ guess about the future. Predictions of outcomes, based upon modeling rules for, as examples, market share, investment, risk, competitive position, etc. are a needed additional facility for business decisions and gaming analysis.

An additional need to improve the efficiency of searching is apparent. In one aspect of searching, the number of queries needed to find the proper collection of information for a study could better be reduced. In another aspect, the results of a study involving many queries could be reused, at least as a basis, or at least by sharing the queries.

The need for currency, best availability, and provision of future, the presence of abstract ttxs presents a significant need for collaboration by many users for refinement to decrease the abstraction toward reality. This leads to the need for consensus building to choose the better of multiple user contributions.

Additional Purposes, Features, and Advantages

Other Advantages

Further objects and advantages of this invention will become apparent from a consideration of the drawings and ensuing descriptions.

Definitions

Definition of terms used herein are given in alphabetical order except where an important relationship exists between terms.

Alerts: As used herein, the term “alert” refers generally to a notification to a user.

Analytic: As used herein, the term “analytic” refers generally to a package of all automation structures put into place to effect automation of categorization.

Appcept: As used herein, the term “appcept” refers to a cnxpt specifically representing an application domain of zero or more technologies.

Application Domain: As used herein, the term “application domain” refers to a family of appcepts. Application domains define the bundle of requirements of a wider range of solutions needed to solve a class of similar problems than what a single specific solution at a specific timeframe would require.

Area of Consideration: As used herein, the term “Area of Consideration” refers generally to a cognitive area of a CMM or of a CMMV virtual map that a user has shown interest by, including but not limited to: a selection, search, query, setting of a ‘goal’, or defining a result set for a goal.

Area of Interest: As used herein, the term “Area of Interest” refers generally to the cnxpts that the user has shown as having an increased probability for being relevant in an Area of Consideration.

Attribute: As used herein, the term “attribute” refers to a property of an info-item.

Authority Control: As used herein, the term “authority control” refers to the library science principle of quality control over index terms for bibliographic material in a catalog to maintain consistency.

Avatar: As used herein, the term “avatar” refers to a specialized Dxo, possibly animated, displayed on a map, including but not limited to: an ‘assistant’ for holding a spot on the map; viewing point of another person currently viewing a visualization; a person or company offering expertise, a service, or a product; other free or paid position objects such as, including but not limited to: reports available, comparisons, or response analytics that can answer questions; a goal; a bubble; or a signpost.

Axpt: As used herein, the term “axpt” refers to a cnxpt specifically representing an application domain of zero or more technologies.

Categorization: As used herein, the term “categorization” refers to a division of items into classes or groups (called categories) according to a particular system including but not limited to: type, semantic meaning, classification, product family, technology sector, parentage, ownership, state of completion, timing, precedence, or TPLs for determining how outmoded or obsolete a technology is, or where gaps in technology exist. Categorizations provide a basis for calculation and modeling, especially for aggregating data or other forms of graphical network calculation. Herein, a category (the destination category) property value may be defined by an equation having as factors, including but not limited to: a value; a reference to a value in a property of a category (the base category); a network property of a base category; a function defined by a map property of the encompassing map or a specified different map; a function defined as a set reference to a property in each association of the set of associations defined by, including but not limited to: to children, from children, to parents, from parents, to siblings, from siblings, from uncles, to uncles, to cousins, from cousins, to categories in a different map, from categories in a different map, etc.; a function defined as a set reference to a property in each category of the set of categories defined by, including but not limited to: categories that are related to a base category, categories that are related to a base category by a specific relationship, including but not limited to: children, parents, siblings, cousins, uncles, nephews, members of sub-tree, members of path to destination category, root of tree including base category, roots of all parents (all leafs in ascending tree), etc. where the base category is in the present map or where the base category is in a specified different map.

Categorization Hierarchy: As used herein, the term “categorization hierarchy” refers to an ordered set of cnxpts within a directed graph, according to rules specified for the zero or more fxxts specified.

Characteristic: As used herein, the term “characteristic”, “cnxpt characteristic” or “ttx characteristic” refers to an expansive set of assertions tending to describe a ttx, assigned to a cnxpt or a ttx.

Cntexxt: As used herein, the term “cntexxt” refers generally to a cognitive area of a CMM and thus includes the ttxs therein. A cntexxt is defined by a parent category represented by a cnxpt where all of the ttxs under consideration are represented by children or grandchildren cnxpts of the parent cnxpt.

Cnxpt: As used herein, the term “cnxpt” refers to a semantic device similar to the ‘concept’ in the Topic Map Standard. The Topic Map Standard ‘topic’ is similar to the cnxpt, but more general. The term concept is too general to be used in the following. Generally, concepts are ttxs represented by cnxpts.

Cnxpt categorization: As used herein, the term “cnxpt categorization” refers to a division of the cnxpts into classes or groups according to their use in an arrangement caused by a set of zero or more association relationships. In one embodiment, cnxpt categories are ‘soft’ in that cnxpts are susceptible of becoming alternative categories or members of alternative categories. Because a cnxpt is a ttx, a cnxpt may be categorized by a ttx category.

Collocation: As used herein, the term “collocation” is used in its “co-location” sense, referring to the act of positioning dxos close together, in a grouping, or into a certain order in a visualization to indicate, including, but not limited to: similarity of meaning, common purpose, common membership, common interest, or common categorization. Collocation is also used to convey the combination, for summarization, of similar cnxpts into a single representative object.

Commonplace: As used herein, the term “commonplace” refers to a knowledge base tuned to capture the ttxs imagined by creative thinkers and to efficiently provide detailed information to innovation and intellectual property workers about those ttxs to share, search, discuss, base calculations on, stay current with.

Common Mental Map: As used herein, the term “Common Mental Map” (“CMM”) (sometimes referred to in the literature as a Collective Mental Map) refers to a shared collection of explanatory constructs, or a commonplace, that individuals can use to make connections with their own cognitive categories and which contains a common understanding of a domain of knowledge used to facilitate dialogue. The CMM, a specialization of a term of art, refers to the collection of data used as a basis for forming maps rather than a graphical or textual map itself.

Common Mental Map Database (CMMDB): As used herein, the term “Common Mental Map Database” (CMMDB) refers to a stored collection of explanatory constructs making up a CMM, and all structural control and website data necessary for establishing and controlling the system.

Consensus Determination: As used herein, the term “consensus determination” refers to the process of forming a consensus result based upon fxxt analysis and results from, including, but not limited to: identity indicator based subject identification, categorization, and merger. The consensus would be an ‘objective’ opinion if it is a combination of opinions of two or more users regarding the veracity and strength of associations and regarding the veracity and importance of cnxpts. The consensus would be a ‘subjective’ opinion if it stems only from opinions of one user regarding the veracity and strength of associations and regarding the veracity and importance of cnxpts, where that specific user expressed an opinion regarding the veracity and strength of that association or the veracity and importance of that cnxpt. Mixed opinion based subjective opinions allow for a combined objective opinion and subjective opinion where an additive formula controls the mixture to provide a coefficient (say ‘q’) multiplier of the subjective opinion plus a coefficient (‘1−q’) multiplier of the objective opinion for any given association's veracity or strength or for any given cnxpt's veracity and importance, the calculation performed prior to the tree extraction process.

Correspondence: As used herein, the term “correspondence” refers to the degree of correctness of the definition of a txo as compared to the tpx it represents.

Crawling: As used herein, the term “crawling” refers to the process of browsing the World Wide Web, a heterogeneous repository, or document management systems in a methodical, automated manner to analyze data on web pages or in corporate documents and to scrape information for import into the CMMDB. As used herein, the term “crawling” also refers to the specification of what to crawl, including how, when, and other parameters for controlling the process. As used herein, the term “crawling instance” refers to one execution of a crawling.

Crawl Result: As used herein, the term “crawl result” is a system construct created when a user begins a new search for a ttx. Crawl results represent an uncharacterized set of information resources collected during a crawling (or scraping). A user defines a ‘crawling’ to find information resources.

Crowd Sourcing: As used herein, the term “crowd sourcing” refers generally to the act of outsourcing the tasks of, including, but not limited to: ideation, collaboration, prediction (wisdom of crowds), valuation (options market pricing), surveying (crowd questions) and investment (crowd funding), to a wide user community (the “crowd”) to tap into the collective intelligence of the public at large to speed innovation and creativity of other users and to reduce overall costs.

Dxos: As used herein, the term “dxo” refers to a type of info-item: that may be displayed by the system in a visualization of any nature; that may represent any thing whatsoever, regardless of whether it exists or has any other specific characteristics; about which anything whatsoever may be asserted by any means whatsoever. A dxo is not a Topic as defined in the TNMS, but rather the base class in the display object structure, from which other displayed objects are sub-classed in a multiple inheritance object structure where either txos or relationships are the other base class.

Alias-hyperlink Dxos: As used herein, the term “alias-hyperlink dxo” or “hyperlink dxo” refers to any of various types of dxos used to show that a dxo, txo or cnxpt would be seen at the location on a visualization or list except that it already exists in the visualization or list another location.

Display Object Inheritance Hierarchy: As used herein, the term “display object inheritance hierarchy” refers to an ordered set of info-item subclasses and superclasses. The objects of the subclass behave, subject to the restrictions of the specialization, like objects of the superclass. Here, the dxo is but one base class in the multiple inheritance structure.

Features: As used herein, the term “feature” refers to a cncpttrrt of a tcept that a user or engineer may use to describe a tcept, product, or its abilities.

Fuzzy Ttx Identification for Collocation: To promote the ability to see ‘nearly identical’ ttxs to allow crowd sourced cleanup or to highlight interesting differences, the system must achieve a “collocation objective.” To do so, one or more of five methods may be utilized to obtain additional identity indicators: to measure the semantic difference between two ttxs; to accept arrangement information from users stating that the ttx is a sub-ttx of another; to accept similarity or differentiation information from users stating that the ttx is similar/identical to another or that there is a definable difference between them; or to accept relevance information from users stating that some information external to the ttx is relevant to describing the ttx.

Fxxt Based

Fxxt based modeling rule formulas are applied on the relationships as mentioned, but note that depending upon the fxxt chosen (or calculated according to a definition), the relationships may apply in different directions depending upon how the Descendant Trees are formed, since directionality does not have to be stated on relationships of this nature, and the endpoint that is a child is determined from the result of the Spanning Tree operation for the Descendant Tree. That means that in one fxxt a sum of children could be of one set, while in another, the sum could be of another set of children.

Fxxt Specified

Modeling rule formulas for relationships may be specified to be applied on the relationships of an infxtypx globally, by scopx, or on a relationship directly (single relationship specific), by relationship scopx in fxxt specifications on a specific fxxt calculation step of the fxxt specification or globally for the fxxt.

Fxxt specified modeling rule formulas for cnxpts (or, in some cases, txos) may be specified to be applied on the cnxpts (txos) of an infxtypx globally, by scopx, or be specified for a type of cnxpt or a single cnxpt instance (txo) directly (single cnxpt (txo) specific), by scopx or infxtypx, or to be applied in fxxt specifications on a specific fxxt calculation step of the fxxt specification or globally for the fxxt.

Map: As used herein, the term “map” refers both to the visualizations which result from the mapping process, as well as the information held in the CMM which is used as a basis for the mapping process. A fxxt may be used to provide context for the organization of the map. A list of tpx info-items may be used as a top level for a map in a portfolio.

Ttx Map: As used herein, the term “ttx map” refers to a visual aid for understanding ttxs and their interrelationships as developed from and based upon the contents of the CMMDB by at least one Ttx Mapping Visualization Process.

Descendent Map: As used herein, the term “descendent map” refers to a visualization supporting a fly-through from general categories to very detailed cnxpts. In one embodiment, maps are often three-dimensional hierarchies. For normal use, a ‘descendent’ taxonometric tree is extracted from the ontology of the CMMDB to form a clump that will provide the information needed to produce a ‘descendant’ fly-through map from general categories to very detailed cnxpts deep within those categories.

Ascendant Map: As used herein, the term “ascendant map” refers to a visualization supporting a fly-through from very detailed cnxpts to general categories such that the multiple categories a cnxpt is a member of, if it is, are viewable. In one embodiment, the ‘descendent’ extract is a forest of trees but the ontology is N-dimensional. Because of this, it is possible that for some cnxpt deep within the ‘descendent’ extracted tree, that the cnxpt or its ancestors will have multiple parents. For such a cnxpt, an ‘ascendant’ tree could be formed where the cnxpt is a root for the tree, where the first branches from the root connect to all of the parents (nodes on other end of the reversed directed edges), where branches from those parents connect to all their parents in turn, etc., and the leaves are the most general categories in the ancestry. This tree would be the basis of an ‘ascendant’ map.

Result Set Map, Selection Set Map: As used herein, the term “Result Set Map Object” or “Selection Set Map Object” refer to visual aids for understanding info-items and their interrelationships as developed from and based upon the contents of the CMMDB by at least one Set Mapping Visualization Process.

Area Map: As used herein, the term “Area Map Object” refers to visual aids for understanding info-items and their interrelationships as developed from and based upon the contents of the CMMDB by at least one Set Mapping Visualization Process operating upon an Area of Consideration or an Area of Interest.

Portfolio Map: As used herein, the term “Portfolio Map” refers to visual aids for understanding info-items and their interrelationships. Each portfolio is a collection of cnxpts of a set type marked with a set fxxt for the portfolio. The highest level of the portfolio is a list of tpx info-items. The cnxpts related to a tpx info-item in the list and within the fxxt of the portfolio are in a map accessible via the list item. Each portfolio fxxt is ‘built’ starting with this initial collection and augmented, as specified in the fxxt specification, with other info-items. The map formed contains all of the cnxpts related to the list items and in the fxxt, but is subdivided according to the list to show the cnxpts by the list items.

Mapping: As used herein, the term “mapping” refers to the process of forming a textual or graphic image to convey information about ttxs, other dxos, and the relationships between them. The visualization of the map is a communications medium that provides a sense of co-location based upon an underlying nearness of the pictured ttxs and display objects based upon the strength of relationships between the cnxpts or dxos representing the displayed objects. The map user “reads” the visualization of the map and interprets its information content in the context of his or her own objectives and knowledge of the knowledge domain and the real or abstract relationships that the map is intended to describe. In this way, the visualization of the map is an outward manifestation of the map, so the visualization of the map is a map. For this reason, here the use of the word map refers both to the information prior to the mapping process and the result.

Maps and Communication

Map Development for User Expectations

To form a map, spatial relationships among the individual pieces of data have to be set, since the ttxs have no geographic nature. The positions are developed based upon the relationship information present and by fxxt analysis, Merger and Comparison, and ontology reduction.

Focusing can be accomplished in many ways. When contexts are categories and the categories have sub-categories, then the focusing can be accomplished by moving from a display of the categories to a display of one (or more) category's sub-categories.

When two or more map visualizations are displayed by a user, the user may select a cnxpt info-item on one map and “sync” one or more other visualizations in order to move the focus of display of the other map to be the cnxpt selected on the first, regardless of the fxxt of the other map. If that cnxpt is not on the other map, the focus is moved to a cnxpt in the fxxt of the other map where the cnxpt is a parent of the selected cnxpt in the first map. If the focus cannot be moved because a cnxpt cannot be found to serve as the focus, then the user is informed. Other info-items may be focused upon.

Different maps may be formed for different fxxts. Multiple types of visualizations provide for the display of the various relationships held in the Map. Each visualization type emphasizes a certain set of relationships between cnxpts as defined by the fxxt specification. A visualization of cnxpts based upon nation of invention will be very different from a visualization of cnxpts ordered by field of study only (unless, of course, the countries are focused on specific technologies and monopolize research on them). Each visualization type generalizes the information available from the Map, omitting certain features from the display to simplify and rapidly convey the context of the content.

Maps in this System

In one embodiment, the map can be re-arranged and new objects can be created, or ‘concretized’. Context-clicking anywhere on the map screen allows the addition of a new ttx, either by starting a goal, or new query within a goal, or by providing a shell for a ttx to be described. It is also possible to create mashups on the visualizations, adding, including but not limited to: knowledge in the form of links, videos, text, web pages, figures, tables, graphics and sound. Ttxs are linked easily to other ttxs to define relationships when the user drags them into another map or list in another window. This information is entered into the CMMDB that the map is derived from, so the map is updated.

As a tool rather than a theoretically oriented system, this system must recognize that: 1) at times, n-ary relationships in the database would allow for ‘high dimensionality (n-ary) Gaussian distance metric or Gaussian similarity measure calculations (based upon Euclidean distance calculations); 2) but as a practical reality, the user can be perfectly happy if presented with a map based upon “strongest dimension at a time” calculations of positioning, 3) that as a practical matter the user cannot be forced to add cnxpts into user determined positions that are fully specified with values for each of a high number of dimensions, and 4) there are anticipated to be a large number of poorly specified positionings done by users to get a map to the point of usefulness quickly. The user must be given a tool that can make use of the high dimension data when it is available but remember that their use of the tool is mainly as a thinker and creator that will place some cnxpt on the map and then move it as needed, or leave more fine grained estimates in one or more important dimensions to others.

In one embodiment, maps can be shared and collaborated upon. View positions and tours (animations showing the process of navigation) of maps may be sent to other users. Written collaboration discussions are retained by the use of votes and discussion threads that can be seen reflected on the map.

Maps by Age

Maps are based upon data from a fxxt as extracted from the CMMDB. In an example of a fxxt, in one embodiment, a map of ttxs anticipated to exist at a set time in the future may be available. As an example of the utilization of dxo personalities and graphical representations, this same map may be displayed in a way that the user will see mannerisms manifested by the personalities of the dxos on the visualization in a way that actions taken by the user within the visualization may cause reactions from the dxos.

Value of Maps

The work of many people goes into each map. Since the map is constructed from data that is obtained from many sources, only small additions to the map (through the CMMDB) will have to be constructed by any individual. This is a form of reuse of prior contributor's efforts.

Data can be collected by importing other categorizations and rationally merging it with existing conceptual information based upon the expertise weighted voting and consensus facility. Maps can be exported for use in organizing other work and for driving drill down analysis in areas such as competitive intelligence and prior art studies.

Mapping by Ttx and Ttx Mapping Design Process: As used herein, the term “ttx mapping” and “ttx mapping design process” refer to a specific design process for developing visual aids for understanding ttxs and their interrelationships. In one embodiment, the Ttx Mapping Design Process will produce one or more designs for visualizations of the ttxs in the CMM, involving but not limited to: dxo positioning, dxo behavior, visualization selection, and visualization content design. In one embodiment, the Ttx Mapping Design Process will produce one or more designs for visualizations of the cnxpts in the CMMDB.

Mapping Relationship: As used herein, the term “mapping relationship” or “mapping function” serves similarly to the mathematical concept of function. A mapping relationship can be thought of as an edge that is also a computing stage that takes an input and produces a single output. For example, a temperature mapping relationship takes an object as input and returns the temperature of that object. A mapping relationship that represents a function that could return multiple objects can instead return a single object representing a single set containing those objects. Mapping relationships, like other relationships, associate two txo info-items.

Traditional mapping relationships have directionality to show that they perform a computation from one object to another, but this directedness is not presumed in this invention, since fxxt specifications may provide roll-ups of various natures and mapping relationships may be used to effect them, resulting in a different directionality in different fxxts.

Matching, Merger and Comparison: As used herein, the term “matching, merger and comparison” refers to the three main processes for automatically determining semantic closeness and reducing the number of info-items a user would see as redundant in a map derived from the CMM. When multiple users concretize ttxs, inevitably there will be redundancy. It may be due to language, laziness, low expertise, etc., but the important contributions users make will usually contain indications of the differences in the ttxs. These differences, or disagreements must be addressed over time, without delaying a user in their work. The automatic operations attempt preliminary actions to work with or around the less than perfect information, and also prepare ‘ticklers’ or ‘to do’ items to provide an opportunity to have a human (one of the crowd) work to review the differences to repair them at a later time.

Merger: As used herein, the term “merger” or “txo merger” refers to the process of merging two info-items (esp. txos) that are known to represent the same ‘thing’ (esp. the same tpx). The CMMSYS facilitates merging of info-items without requiring the merged info-items to be copied or modified. Merging occurs prior to and without regard to fxxt analysis.

Identifying when two infrastructure txos represent the same tpx is achieved by applying heuristics without weights and without regard to fxxts:

-   -   If an administrative user has stated that two infrastructure         txos represent the same tpx, then the two are combined, subject         to undo, and the transaction is recorded, so long as the         authority of the user is sufficient.     -   If an administrative user has stated that one infrastructure txo         represents a member of a category or a sub-class of another         txo's tpx, then a directed relationship between the two is         created, subject to undo, and the transaction is recorded, so         long as the authority of the user is sufficient.     -   If two txos have a subject identifier occurrence relationship         with an ‘absolute highest’ weighting to the same specific         subject indicator irxt, then they both identify, as a subject         locator, the same network resource as being the thing that they         represent and must be merged (so long as the subject locator         resolves to a web resource which has not changed between the         time the txos were created and the present).     -   If two irxts share the same source locator, then they should be         considered to represent the same tpx but only if the locator         resolves to the same page, document content consistently over         time.

Matching: As used herein, the term “matching” refers generally to the setting of a value for the closeness of in meaning between two info-items of the same type to provide an identity indicator.

Trait and Suitability Matching: As used herein, the term “trait matching” or specifically “cncpttrrts matching” refers generally to the setting of a value for the closeness in meaning between two cncpttrrts. In one embodiment, in the included specializations called “similarity matching” or the deeper specialization “feature matching”, two cncpttrrts are close if they are semantically similar, such as where a cncpttrrt of a car may be ‘tan’, while another car may be ‘light brown’, and those cncpttrrts would thus be given a high value for closeness. In one embodiment, in the specialization called “suitability matching” or “application suitability matching”, closeness is measured by satisfaction rather than similarity. As an example, where an appcept calls for high temperature resistance, and a feature cncpttrrt of a candidate tcept states that the components made from that tcept will melt at room temperature, the trxrt representing the requirement and the feature trxrt represent the tcept's ability will have a very low ‘closeness’ relationship to show that feature fails to meet or satisfy the requirement even though the trxrts each refer to operating temperature.

In one embodiment, where multiple trxrts of a single ttx are similar, as found by users or automatically, a suggestion to users to merge the two trxrts is generated.

In one embodiment, in the specialization called “tpx trait matching”, a trait of an infrastructure txo is compared against a trait of another txo.

Trait and TPL Matching: As used herein, the term “TPL matching” refers generally to the setting of a value for the closeness of an implementation of a technology to a design criterion caused by addressing a TPL (theory, principle, or law of science). In one embodiment, in the included specializations called “conformance to science”, two cncpttrrts are close if the technology trait addressed with significant care a scientific principle and achieved the implemented design to maximize performance with that scientific principle in mind regardless of whether other scientific constraints were also considered in the implementation. An example is the design of a wing where the principles of aerodynamics available at a specific timeframe were considered. A match would exist between the traits of the wing such as the surface design and specific principles of aerodynamics. A match might not exist or be considered strong between a principle of aerodynamics that was disruptive to the field and was discovered far after the design of the wing occurred. In one embodiment, in the specialization called “conformance to science”, closeness is measured by satisfaction rather than similarity. As an example, where an law of science describes high speed flight and a plane is ill-designed for it due to other factors such as a requirement for low fuel consumption, the trxrt representing the “conformance to science” and the feature trxrt represent the tcept's ability to fly fast will have a very low ‘closeness’ relationship to show that feature was not designed to answer the scientific principle.

Semantic Matching: As used herein, the term “semantic matching” refers generally matching of info-items on the basis of semantic distance calculations on their descriptions. Where the descriptions of two ttxs are very close semantically, then the two are matched, and, in one embodiment, a suggestion to users to merge the two ttxs is generated.

Interest Matching: As used herein, the term “interest matching” refers generally to assessing the closeness of two ttxs where a number of users who have stated a similar search goal normally visited a specific set of ttxs, implying that they found that the specific set of ttxs were apparently relevant to their goal. Where users often visit, somewhat equally, one or another of two ttxs after stating similar goals, in one embodiment, a suggestion to users to merge the two ttxs is generated.

Comparison: As used herein, the term “comparison”, “cnxpt merger” or “cnxpt comparison” refers to the process of determining if two cnxpts represent the same ttx. Comparison is based upon a resolved fxxt (a derived ontology resulting from a fxxt analysis). Because of the dependence upon the fxxt analysis process, it is impossible to state that two cnxpts represent the same ttx in all circumstances unless all fxxts would allow that conclusion.

In one embodiment, the CMMDB will, at one point or another, contain info-items that appear to represent the same ttx. In one embodiment, the CMMDB will, at one point or another, contain occurrences related to two or more info-items. The info-items in each case might appropriately be merged, or it may be premature to merge the info-items until it is quite clear that no differential in meaning represented is present.

In one embodiment, a single cnxpt results from combining the characteristics of the two cnxpts only if all of the characteristics are the same, but where a substantial disagreement is seen regarding the characteristics of a cnxpt, a suggestion is made that the cnxpt be split into three cnxpts, where one parent is formed from the characteristics in the intersection of characteristics (those agreed upon), and two child cnxpts having the characteristics in dispute on each side.

The matching process is completed prior to comparison, for any given comparison.

Modeling

Modeling and Outcomes

Models: As used herein, the term “model” refers to a prescribed framework for calculating an economic, benefit, or other form of value or prediction. The activity includes planning, constructing, and executing the process for automatically completing the analysis.

Modeling Rules: As used herein, the term “modeling rule” refers to a formula for calculating, including but not limited to compute: the weight of the relationship, expected monetary values, decision analysis with risk/reward, and competitive scenario gaming, based upon CMM data to which they are associated with.

Modeling Rules provide a modeling structure. The definitions may be associated with, including but not limited to: txos, relationships, cnxpts, axpt, txpt, tplxpts, tcepts, appcepts, fields of science, dxos, as well as to spreadsheets attached to those info-items. These connections may be reconfigured to change the basis for the Modeling rule. Modeling Rules may be re-associated to change the basis for the Modeling Rule.

The formulas specified will generally follow the style used for spreadsheet formulas, where relationship infxtypx reference iterators are similar to range specifications and specify, including, but not limited to a: relationship infxtypx, fxxts, scopxs, relationship role, relationship list; and cnxpt infxtypx references are similar to cell specifications and refer to, including, but not limited to: characteristic references, scopxs, cnxpt ranges, cnxpt lists, cnxpt characteristics, fxxts, txos, infxtypxs, txo characteristics, txo lists, and qualifications by txo characteristic.

Calculations are performed on the CMM data based upon, including but not limited to: base data and base assumptions, fxxt definitions, fxxt summarizations, extraction descriptions, primitive's properties, primitive's associated spreadsheets, and ‘Modeling Rule’ descriptions.

In one embodiment, relationships may be mapping functions that serve similarly to the mathematical concept of function. Relationships do not need to specify any particular computation, but may by being used as a mapping relationship.

Outcome: As used herein, the term “outcomes” refer to specifications of modeling conditions that, if met, imply that the outcome will occur. Outcomes provide a result name for calculations for expected monetary values, decision analysis with risk/reward, and competitive scenario gaming. The likelihood of the actuality of the state of the future (or of who will prevail) is calculated based upon the base data and base assumptions, fxxt definitions, fxxt summarizations, extraction descriptions, primitive's properties, primitive's associated spreadsheets, and ‘Modeling Rule’ descriptions.

Relationships

Relationships: As used herein, the term “relationship” refers to an edge in the CMMDB ontology between nodes of specific types, including, but not limited to txos.

Relationships can be asserted conforming to the following rules:

-   -   The roles property shall contain two or more role items, in an         ordered set.     -   In one embodiment, a relationship may have no more than one         ‘from’ role.     -   In one embodiment, a relationship may have no more than one         identifier for any role.

(This definition does not constrain the physical implementation, where a relationship can be implemented in a list of tuples, all under a single entity which occupies one role, or in a relational schema.) Associations are specific specializations of relationships.

Structuring Relationships

Visualization Structuring Propositional Relationships: As used herein, the term “Visualization Structuring Propositional Relationships” refers generally to a system of relationships needed to extract a visualization from the CMM. Each knowledge domain has more specific relationships, but those relationships, when summarized, must provide a set of specific relationships:

-   -   A ttx is more specific and included in the parent ttx         (subsumption, categorization, classification).     -   A ttx is similar or equivalent to another ttx.

Knowledge Domain Centric Visualization Structuring Propositional Relationships

Knowledge Domain Centric Visualization Structuring Propositional Relationships in the CMM for technology mapping will at least include the following types:

-   -   A ttx is more specific and included in the parent ttx         (subsumption, categorization, classification).     -   A tcept was invented later than its parent (parent is potential         prior art)     -   A tcept was based upon a dependent claim stemming from one of         the claims that could ‘read on’ its parent.     -   A ttx was defined (originally mentioned) in relevant information         resources that cited the articles defining the parent.     -   A ttx was entered as a query (by a user) with a starting point         of the parent.     -   A ttx was moved or pasted as a child of the parent.     -   A ttx is somehow related to the parent (partitive—part of).     -   A ttx is somehow related to another ttx.     -   A ttx is similar or equivalent to another ttx.

Associations

Ttx Associations: As used herein, the term “association”, “ttx relationship”, or “cnxpt relationship” refers generally to a infxtypxd relationship representing an n-ary aggregate of cnxpts. Associations are the general form for the representation of relationships between cnxpts. That is, an association is a grouping of cnxpts with no implied direction or order, and there is no restriction on the number of cnxpts that can be grouped together.

Associations are given a different name from the general set of relationships so that less confusion will result. For instance, there are relationships that do not connect to ttxs, but do connect parts of speech, of the nature described by Noam Chomsky and many others. Those are certainly useful constructs and could represent actions and description of whole classes of ttx objects here. The analysis of natural language by transforms on those constructs is a front-end process that results here in Syntactically Suggested Associations, below, to obtain information from documents, or to accept commands and value. Also, for use of the present system for outputting information in natural language, a limited language structure can support wide but shallow natural language production.

An association can be assigned a infxtypx that specifies the nature of the relationship represented by the association. In addition, each cnxpt that participates in the association plays an infxtypxd role that specifies the way in which the cnxpt participates.

For example to describe the relationship between a person, “John Smith,” and the company he works for, “ABC Limited,” we would create an association infxtypxd by the cnxpt “Employment” and with role infxtypxs “Employee” (for the role played by “John Smith”) and “Employer” (for the role played by “ABC Limited”).

Associations may be directed, bi-directed, undirected, or symmetrical (optionally directed). They may have a weight associated with them, and may also have other characteristics such as, including but not limited to: infxtypxs, scopxs, values, or attached info-items such as trxrts and purxpts. In one embodiment, the objects at each endpoint of an association have roles as defined collectively by:

-   -   their infxtypx;     -   their scopx;     -   the endpoint of the relationship they are on;     -   the scopx of the relationship;     -   the infxtypx of the relationship; and     -   the fxxt specification being used.

Associations are formal representations of relationships between ttxs, represented by ontology edges between cnxpts that assert the relationship between the two ttxs. Ttx associations are completely independent of whatever information resources may or may not exist or be considered as occurrences of those cnxpts.

Associations can be grouped according to infxtypx, including, but not limited to: categorical, affinitive, other. Ttx associations may have other characteristics such as, including but not limited to: values, scopxs, date applicable, timeframe applicable, horizon applicable, date created, creator, infxtypx.

Associations may be established manually by authorized users. In one embodiment, associations may be established by automated analysis, including but not limited to: semantic distance calculation, relevance analysis.

The Ttx association between two cnxpts can be asserted using an association that conforms to the rules for all relationships, and the following:

-   -   The type property shall be set to a Ttx Association type.     -   For categorical, classification, membership, or other hierarchy         associations, the first roles (the ‘from’ role) will be the type         or parent and the second (the ‘to’ role) is the instance or         child. For affinitive associations, the role order for the first         two roles has no meaning except in quasi-symmetrical affinitive         associations (husband and wife are roles for ‘married-to’         relationship).     -   A fxxt may be specified for the Ttx association.

Scopx applies to this association type in the same way as it does to any other.

Association Roles

Each cnxpt that participates in an association has a corresponding association role which states the role played by the cnxpt in the association. In the case of the relationship Fred was born in Canada, expressed by the association between Fred and Canada, those roles might be person and birthplace. Roles may become acceptable endpoint types for an association type in a Fxxt Specification.

Association Direction

Associations may be directed, quasi-symmetrical, or symmetrical in the sense that in a symmetrical relationship the nature of the relationship is the same whichever way you look at it. Associations are symmetrical in the sense that the strength of the relationship is the same either way it is viewed. For example, a directed association is present where a cnxpt is in a category represented by a second cnxpt. An example of a symmetric association is collaboration, so that the corollary of “Lorca collaborated with de Falla” would (likely) be that “de Falla collaborated with Lorca”. Sometimes the anchor roles in a symmetrical relationships are the same (in this case: collaborator and collaborator), sometimes they are different (as in the case of the husband and wife roles in a married-to quasi-symmetrical affinitive association).

Association Transitivity

Other association types, such as those that express class/instance and part/whole (meronymy/holonymy) relationships, are transitive: If we say that Lorca is a poet, and that a poet is a writer, we have implicitly said that Lorca is a writer. Similarly, by asserting that Granada is in Andalusia, and that Andalusia is in Spain, we have automatically asserted that Granada is in Spain and any Topic Map-aware search engine should be able to draw the necessary conclusions without the need for making the assertion explicitly.

Ttx Categorical, Classification, Membership, Hierarchy, Type-Instance, Class-Instance Relationships: As used herein, the term “hierarchical relationship”, “categorical association”, “classification association”, “membership association”, or “hierarchical association” refer to a infxtypxd relationships each representing a parent child relationship, and collectively forming hierarchies. Hierarchical relationships are of several kinds, the primary ones being: genus/species and whole/part. When used to describe relationships between cnxpts here, the “hierarchical association” specialization is most accurate.

The classic rule for validity in hierarchical relationships may be stated as: “Terms are hierarchically related only if both are members of the same fundamental category (fxxt); that is, they represent entities, activities, agents, or properties, etc.” Here, “subjective” hierarchies created by consensus building by votes and crowdsourcing cause this rule to be violated and the CMM is thus more adaptable.

Ttx categorical, classification, subsumption, membership, hierarchy, Type-Instance, and Class-Instance relationships may be established manually by authorized users.

Hierarchical—Broader/Narrower Term (BT/NT): As used herein, the term “hierarchical

-   -   broader/narrower term”, or “BT/NT” refer to a infxtypxd         relationship expressing a hierarchical relationship based on         levels of superordination and subordination, where the         superordinate term represents a class or a whole and is labeled         as the broader term (BT), and subordinate terms refer to its         parts, or narrower aspects of the class (NT).

Broader Term (BT) and Narrower Term (NT) relationships are shown through hierarchies in classified tools and with Broader and Narrower Term codes in alphabetical tools.

Hierarchical—Partitive (Whole—Part): As used herein, the term “hierarchical—Partitive”, or “Whole—Part” refer to a infxtypxd relationship expressing a hierarchical relationship between tpxs of the same type, where ‘the name of the part implies the name of the possessing whole in any context’. Here, the CMM is open to allow more partitive relationships, but ISO 2788 currently allows just four partitive cases:

-   -   Systems and organs of the body     -   Geographical location or containment—‘is in’, ‘born in’     -   Discipline (or field of study)     -   Social structures

Ttx Type-Instance Association

In one embodiment, the type-instance association, stating that a ttx is an instance of another ttx, is asserted using a scopxd association between cnxpts. Instances may include ‘Variant of a Technology’ where the ‘Class’ is the ttx defining the tcept and the Variant tcept is the ‘Instance’.

Cycles in this relationship are allowed, and should be interpreted to mean merely that different rationales exist for the inclusion of one ttx as represented by a cnxpt into a category as represented by another cnxpt, where one rationale conflicts with another.

The type-instance association is not transitive. That is, if B is an instance of the type A, and C is an instance of the type B, it does not follow that C is an instance of A.

Temporal Order Association: As used herein, the term “temporal order association” refers to an infxtypxd binary relationship between cnxpts that reflects a relationship based upon whether one cnxpt occurred or will occur after another cnxpts. Example: “steel furnaces occurred after copper smelting techniques”.

Cause and Effect Association: As used herein, the term “cause and effect association” refers to an infxtypxd binary relationship between cnxpts that reflects a relationship based upon whether a ttx was the cause for another or effected another ttx. Example: “is propulsion of”.

Ttx citation (cited-citing) Associations: As used herein, the term “ttx citation association” or “ttx citation hierarchical association” refers to an infxtypxd binary relationship between cnxpts that represents the referencing or citation in a description of one ttx (the citing ttx) of the other ttx (the cited ttx as a whole) by specific referencing of the cnxpt's description (as a whole). A ttx citation association is a directed association, but not necessarily a reliable hierarchical association. Specializations of the ttx citation association provide for heightened accuracy based upon the nature of the citations and references and who created them. Ttx citation associations are given weights, depending upon the nature of the citation. Where a high weight is provided, the relationship is seen as more reliable as a hierarchical association, and is interpreted as a “ttx citation hierarchical association”.

The reference may be in the form of a “ttx description content reference citation association”. Any citation in a “ttx description content author-placed reference citation tag” found may only serve as a basis for a weaker association and thus are not to be considered as a basis for a hierarchical association, unless the user specifically states a very high weight.

In the general case, the cited ttx, or at least something seemingly related to it, must have been known by the author of the citing ttx description. Because an inference or presumption could be made that the cited ttx existed before the citing ttx, a “ttx citation association” representing that the cited ttx's cnxpt was relevant to the citing ttx's cnxpt is appropriate and relevant, and a “ttx citation hierarchical association” representing that the cited ttx's cnxpt was a predecessor (or category) of the citing ttx's cnxpt may be appropriate and relevant. Weights assigned are established by system parameters set and altered over time and the nature of the reference.

Ttx citation associations may be established manually by authorized users with restrictions.

The ttx citation association is not based upon any occurrence relationship. A different form of hierarchical association called an “imputed cnxpt citation association” is automatically created, prior to map generation, between cnxpts based upon citations between occurrence items.

Ttx Description Content Reference Citation Associations: As used herein, the term “ttx description content reference citation association” refers to an infxtypxd binary relationship between cnxpts that represents the referencing or citation in a description of one ttx (the citing ttx) of specific content in another ttx's cnxpt's description by specific citation. It is a specialization of a “ttx citation association”.

The cited cnxpt description must have been known by the author of the citing ttx description. Because the cited ttx existed before the citing ttx, a “ttx description content reference citation association” representing that the cited ttx's cnxpt was a predecessor (or category) of the citing ttx's cnxpt is appropriate and relevant. Ttx description content reference citation associations are given substantially higher effective weights than other ttx citation associations. Weights assigned are established by system parameters set and altered over time and the nature of the reference.

Ttx description content reference citation associations may be established manually by authorized users only where a translated name is in the citing document because it would not be caught automatically.

Cnxpt Name Reference Citation Associations: As used herein, the term “cnxpt name reference citation association” refers to an infxtypxd binary relationship between cnxpts that represents the referencing or citation in a description of one ttx (the citing ttx) of the name of another ttx's cnxpt (the cited ttx) by specific use. It is a specialization of a “ttx citation association”.

The cited ttx, or at least something seemingly related to it by common name, must have been known by the author of the citing ttx description. Because a presumption could be made that the cited ttx existed before the citing ttx, a “cnxpt name reference citation association” representing that the cited ttx's cnxpt was a predecessor (or category) of the citing ttx's cnxpt is appropriate and relevant. Cnxpt name reference citation associations are given medium weights. Weights assigned are established by system parameters set and altered over time and the nature of the reference.

Cnxpt name reference citation associations may be established manually by authorized users only where a translated name is in the citing document because it would not be caught automatically.

Ttx Description Content Later-Added Reference Citation Associations: As used herein, the term “ttx description content later-added reference citation association” refers to an infxtypxd binary relationship between cnxpts that represents the referencing or citation in a description of one ttx (the citing ttx) of specific content in another ttx's cnxpt's description by specific citation added later by an authorized user. It is a specialization of a “ttx citation association”.

The cited cnxpt description might have been known by the author of the citing ttx description, but no inference can be made to that. Instead, only a weaker presumption, based upon a user's analysis and a manifestation of a belief, can be made to establish a “ttx description content reference citation association” representing that the cited ttx's cnxpt was a predecessor (or category) of the citing ttx's cnxpt is appropriate and relevant. Ttx description content reference citation associations are given slightly higher effective weights than a “cnxpt name reference citation association”. Weights assigned are established by system parameters set and altered over time and the nature of the reference, but a user may state a higher weight.

Ttx description content reference citation associations may be established manually by authorized users only where a translated name is in the citing document because it would not be caught automatically.

Discontinuity in Innovation Association: As used herein, the term “discontinuity in innovation association” refers to an infxtypxd, directed, binary relationship between txpts that reflects a relationship based upon whether a tcept was the discontinuous successor for another tcept. Examples: “personal computers were the replacement technology for manual typewriters”; “digital electronic imaging has substituted for Daguerreotypes”. In one embodiment, the discontinuity in innovation association refers to an infxtypxd, directed, ternary association between two txpts and one appcept that reflects a relationship based upon whether a tcept was the discontinuous successor for another tcept where addressing a need stated by an appcept. Examples: “personal computers were the replacement technology for manual typewriters for production of correspondence, creating broader market”; “digital electronic imaging has substituted for Daguerreotypes for family photography, as a substitute”.

The nature of the discontinuity is an important attribute or trait of the discontinuity in innovation association, stating, including but not limited to: is the discontinuity a substitution, create a broader market, affects competitive competences.

Technological innovation is not entirely incremental. Disruptive tcepts may substitute for a certain appcept, may solve a wider requirement than for a specific appcept, and may enhance or destroy the competence established firms have in an appcept family. Periods of market continuity, during which innovation is incremental, and rates of innovation remain steady, and significant product or market changes are infrequent, may end abruptly, giving way to periods of discontinuity, where businesses transform or die, new businesses thrive, and major product and process changes occur.

Field of Study Association: As used herein, the term “Field of Study Association” refers to an infxtypxd binary relationship between cnxpts that reflects a relationship based upon whether a ttx is taught in a particular field of study that is described as another ttx. This is a directional association.

For example, ‘computer programming techniques’ are taught in engineering, mathematics, business, etc. This would illustrate that those three fields of study are related indirectly by the second level of a hierarchy consisting of a ttx called ‘computer programming techniques’.

Instruments Association: As used herein, the term “Instruments association” refers to an infxtypxd binary relationship between cnxpts that reflects a relationship based upon whether a ttx was instrumental in producing another ttx. This relationship states that one ttx facilitates another. (teaching—overhead projectors).

Materials Association: As used herein, the term “materials Association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon whether a ttx defined a material used in another. Materials Associations state that one ttx is used to construct another. Example: plastic film-transparencies.

Product of or By-product of Association: As used herein, the term “product of or by-product of Association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon whether a ttx was a “product of” or “by-product of” another. This relationship states that one ttx is produced by another, hence requiring a parent-child direction.

Satisfies Requirements Association: As used herein, the term “Satisfies Requirements Association” refers to a weighted, scopxd, infxtypxd binary relationship between cnxpts that reflects a relationship based upon whether and the degree to which a tcept will satisfy requirements as stated for an appcept. This association states that a tcept can be used to solve the needed function for an appcept's purpose. The weight is a projection or an entered estimate of the ability to solve the requirements successfully relative to all other competitive tcepts. This association may be added manually or automatically based upon trait matching. It is directional.

Subsumption Associations: As used herein, the term “subsumption Association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon whether a ttx is more specific and included in the parent ttx (subsumption, categorization, classification). This is a general form where a more specific reasoning for a more specific scopx and infxtypx of relationship may not be available. This could be the case when a categorization from another source is being used directly. This is a directional relationship.

Document-Retrieval Definition of Subsumption Association: As used herein, the term “document-retrieval subsumption Association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon whether a ttx is narrower than its parent according to the document-retrieval definition of ‘broader-narrower’:

“Ttx A is broader than ttx B whenever the following holds: in any inclusive search for A all items dealing with B should be found. Conversely B is narrower than A.”

This is a directional relationship. This definition introduces subjectivity. Concrete hierarchical links are backed up by a majority count based on expert judgments or an analysis of search requests.

Extensional Definition of Subsumption Association: As used herein, the term “extensional subsumption Association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon whether a ttx is narrower than its parent according to “logical considerations”. These occur when other labels for ‘broader-narrower’ such as “genus-species” or “is kind of (for ‘broader’) are used to characterize the generic hierarchy relation. This is a directional relationship.

Intensional Definition of Subsumption Association: As used herein, the term “intensional subsumption Association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon whether a ttx contains all the attribute values of the broader ttx plus at least one in addition.

This is based upon the German standard formulation of generic subsumption based on the representation of ttxs as sets of property or attribute values. This is a directional relationship.

Subclass Hierarchical Associations

Supertype-Subtype Hierarchical Association: As used herein, the term “ttx supertype-subtype relationship” refers to an infxtypxd binary relationship between cnxpts that represent a relationship between a more general ttx (the supertype) and a specialization of that ttx (the subtype) within a scopx and fxxt. This relationship states that a ttx is a subclass or a superclass of another ttx. This is a directional relationship. Example: Instance of John F. Kennedy is an instance of Person, which implies that he is also an instance of Living Thing. The converse is not necessarily true. A type may have any number of subtypes and supertypes. The supertype-subtype relationship is transitive, which means that if B is a subtype of A, and C a subtype of B, C is also a subtype of A. Example of ‘is subclass of’: Pope is subclass of Person, and Person is a subclass of Living Thing, etc.

Cycles in each of these relationships are allowed, and (contrary to TNMS) must not be interpreted to mean that the sets of ttxs included in the relationships are in any way the same.

Category-Member Hierarchical Association: As used herein, the term “ttx category-member hierarchical association” refers to an infxtypxd binary relationship between cnxpts that represent a relationship between a category of ttxs (a categorization or classification) and a member of that category (another classification or the member ttx) within a scopx and fxxt. The converse is not necessarily true. A category may have any number of members and supertypes. Example of ‘is component of’: CPU is a component of Computer, etc. (express part-to-whole relations)

The category-member relationship is transitive, which means that if B is a member of A, and C a member of B, C is also a member of A albeit indirectly through B. The category-member-subtype relationship is also transitive, such that if B is the member of A, it follows that every subtype of B is also a member of A. Example of ‘is member of’: Braun is member of Government of Germany, etc.

Predecessor-Successor Hierarchical Associations: As used herein, the term “ttx predecessor-successor hierarchical association” refers to an infxtypxd binary relationship between cnxpts that represent a relationship, within a scopx and fxxt, between a pre-existing ttx (as in prior art for tcepts) and a later defined ttx whether or not stemming from of that pre-existing ttx. A ttx may have any number of predecessors or successors.

Other Subclass—Like Associations

Ttxs may participate in associations which are similar to supertype-subtypes including, but not limited to: General ‘is a’ classifications; Instance (class/instance); Generic (subclass/superclass); Children-Parents, implies (‘is mother of’ implies ‘is parent of’, ‘is parent of’ implies ‘is relative of’) and a number of others.

Custom Hierarchical associations: As used herein, the term “custom hierarchical association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon whether a ttx is somehow related to the parent (defined by some added function). This is a directional relationship.

User Suggested—Ttx Placement Location Associations: As used herein, the term “user suggested—ttx placement location association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon where a ttx was created by or recategorized by a user by placement within the indicated parent cnxpt as representing the parent ttx, suggesting that the parent cnxpt should also be a category if not already one. This is a directional relationship and is a vote. Additional user suggested—ttx placement location associations may be established by an authorized user when the user believes that the cnxpt should be located within a different category.

User Suggested—Goal Establishment Location Association: As used herein, the term “user suggested—goal establishment location association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon where a goal was created or recategorized as within the parent. This is a directional relationship and is a vote. User suggested—goal establishment location associations may be established by authorized users when the user begins a goal by placing the goal initially in an indicated ttx represented by a cnxpt, suggesting that the cnxpt should also be a category if not already one. The goal process may result in the cnxpt that is created being located in a different category, and thus this relationship may move. In one embodiment, the relationship with the cnxpt category representing the original ttx (location) is also retained but given a very low weight.

Affinitive (Related Terms: RTs) Relationships: As used herein, the term “affinitive associations” or “RTs” refers to an infxtypxd binary relationships between cnxpts that represent one of a class of non-hierarchical relationships between ttxs. Affinitive associations are not necessarily directional in nature. At one extreme, an RT may represent nothing more than an extremely vague ‘See-also’ connection between two ttxs. At the other extreme, it would represent absolute and proven equivalence of the two ttxs, within a constraint of a scopx or fxxt. Affinitive associations are NOT considered directed relationships even if they are set to be for some other purpose.

Ttx affinitive associations may have other characteristics such as, including but not limited to: values, scopxs, date applicable, timeframe applicable, horizon applicable, date created, creator, infxtypx.

Affinitive associations state a close or significant semantic relationship between ttxs but one that is not hierarchical and is probably not a statement of absolute equivalence (synonymous). Where two ttxs are equivalent in all scopxs, they are merged, thus an affinitive association will not continue to exist where absolute equivalence is seen by identity.

The utility of utilizing non-hierarchical relationships is that they can provide placement guidance in 3D hierarchical displays of the ontology information. They also provide information for forming fxxts.

Functionally Related Relationship: As used herein, the term “functionally related relationship” refers to an infxtypxd binary relationship between cnxpts that reflect relationships based upon whether a ttx is somehow Functionally Related another ttx. The way it is related is set as a descriptive attribute that cannot be expressed for the other types of relationships.

Concurrent Relationship: As used herein, the term “concurrent relationship” refers generally to infxtypxd binary relationships between cnxpts based upon whether a ttx was concurrent with another or that two ttxs occur at the same time, or between purxpts based upon whether a purlieu was or will be concurrent with another or that two purlieus occur at the same time.

Delay Relationship: As used herein, the term “delay relationship” refers generally to an infxtypxd binary directed relationship stating that a delay must exist between two cnxpts.

Roadblock Relationship: As used herein, the term “roadblock relationship” refers generally to an infxtypxd binary directed relationship stating that a tcept cannot yet stem from another tcept because of an unsolved technical problem. The roadblock relationship will be ‘released’ when the problem is stated to be solved, but the roadblock relationship will be retained for historical analysis.

Gap Relationship: As used herein, the term “gap relationship” refers generally to an infxtypxd binary directed relationship stating that a requirement of an appcept is not yet met by any tcept within a context cnxpt or is more specifically not met by a specific tcept. A stated reason should be attached to the relationship.

Value Strength Relationship: As used herein, the term “value strength relationship” refers generally to an infxtypxd binary directed relationship stating that a value established on one ‘from’ cnxpt may be applied only to the degree set by the strength of the relationship during the use of the ‘from’ cnxpt's value to determine the derived value for the ‘to’ cnxpt.

Coordination Relationship: As used herein, the term “coordination relationship” refers generally to infxtypxd binary relationships between cnxpts based upon whether some coordination such as (sibling: a son—a daughter) or (proton—neutron—electron) exist but where a hierarchy is not present.

Custom Affinitive association: As used herein, the term “custom affinitive association” refers generally to scopxd, infxtypxd binary relationships between cnxpts based upon whether a ttx is subjectively similar or strongly related with another ttx, according to a user. This is a subjective vote toward existence of similarity. A user may add a coefficient to increase or decrease the default weight according to their sense of the strength of similarity, so far as the user is authorized to set. Custom affinitive associations may be established manually by authorized users, or by automated procedures, including but not limited to: analytics. Custom affinitive associations are not specific to fxxts, but may be scopxd based upon a user request or, if discernable, by the scopx embodied by the fxxt being visualized.

Custom Equivalence Relationship: As used herein, the term “custom equivalence relationship” refers generally to scopxd, infxtypxd binary relationships between cnxpts based upon whether a ttx is subjectively equivalent to another ttx, according to a user. This is a subjective vote toward equivalence. This is equivalent to an absolute maximum weighted custom affinitive association, so far as the user is authorized to set. Custom equivalence relationships may be established manually by authorized users or by automated procedures, including but not limited to: analytics. Custom equivalence relationships are not specific to fxxts, but may be scopxd based upon a user request or, if discernable, by the scopx embodied by the fxxt being visualized.

Query in Common Affinitive Associations: As used herein, the term “query in common affinitive association” refers generally to scopxd, directed, infxtypxd binary relationships between cnxpts based upon whether a query used to define one cnxpt has been used to define a second cnxpt. This relationship is not dependent upon the relevance of result set items directly, and is thus a low weighted relationship. The relevance is taken into consideration by occurrence relationships. This is a subjective vote toward equivalence. Query in common affinitive associations are not specific to fxxts or scopxs.

Custom Negative Affinitive Associations: As used herein, the term “custom negative affinitive association” refers generally to scopxd, infxtypxd binary relationships between cnxpts based upon whether a ttx is subjectively dissimilar to another ttx, according to a user. This is a subjective vote toward non-existence of similarity. Custom negative affinitive associations may be established manually by authorized users. A user may add a coefficient to increase or decrease the default weight according to their sense of the strength of dissimilarity, so far as the user is authorized to set. Custom negative affinitive associations are not specific to fxxts, but may be scopxd based upon a user request or, if discernable, by the scopx embodied by the fxxt being visualized.

Genetic Affinitive Associations: As used herein, the term “genetic affinitive association” refers generally to infxtypxd binary relationships between cnxpts based upon whether a ttx containing the same genetic structure but not specifying the actual hierarchical association with another ttx.

Other Affinitive Relationships: As used herein, the term “other affinitive relationship” refers generally to scopxd, infxtypxd binary relationships between cnxpts based upon whether a ttx is subjectively related to another ttx in a particular way, according to a user. This is a subjective vote toward existence of the relationship. A weight based upon the type of relationship is set for the relationship, and a user may add a coefficient to increase or decrease the weight according to their sense of the strength of similarity, so far as the user is authorized to set. These relationships may be established manually by authorized users or by automated procedures, including but not limited to: analytics.

Other Affinitive Relationships include but are not limited to:

-   -   a. Synonymy—“is synonym of” (this could even be used to         implement redirects)     -   b. Hyperlink—“see also”     -   c. Comment     -   d. Lexical Variant     -   e. Quasi-synonyms     -   f Negative—is not like     -   g. Negative—is opposite of     -   h. Is in same category as         -   Terms with overlapping meanings (e.g. Ships and Boats)     -   i. Is in different category from         -   The whole-part affinitive relationship (e.g. Harbors-Wharfs)         -   A discipline or field of study versus the objects or             phenomena studied (e.g. Ornithology-Birds)         -   An operation or process versus the agent or instrument (e.g.             Photocopying-Photocopier)         -   An occupation versus the person in the occupation (e.g.             Nursing-Nurse)         -   An action versus the product of the action (e.g.             Photocopying-Photocopies)         -   An action versus its patient (e.g. Food inspection-Food)         -   Ttxs versus causal dependence (e.g. Explosives-Explosions)         -   A thing or action versus its counter-agent (e.g. Head             injuries-Helmets)         -   Raw material versus product (e.g. Iron ore-Steel)         -   An action versus an associated property (e.g. Food             inspection-Food safety)         -   A ttx versus its opposite (antonym not treated as a             quasi-synonym) (e.g. Imports-Exports)     -   j. Special Relationships exist between Information Resources         linked to ttxs     -   k. Ttxs are Contiguous     -   l. Definitional affinitive relationships     -   m. Meaning overlap affinitive relationships     -   n. Ttxs share Combined ideas     -   o. Unspecified, but affinitive relationships     -   p. Scope issues remain, but one ttx describes a wider meaning         than another ttx

Syntactically Suggested Associations

Syntactically Suggested Associations: As used herein, the term “syntactically suggested association” refers to an infxtypxd binary relationship between cnxpts that represent relationships based upon a syntax deconstruction or interpretation rule or heuristic. These associations may be directional, hierarchical, or affinitive. Syntactically suggested associations may be imputed based upon syntax rules or syntactic relationships suggesting hierarchical relationships, or may be established by an authorized user when the user believes that the syntax suggests an association.

Subject Objects

Ideas—Subjects, Topics, Ttxs

Tpx→Represented by Txo: As used herein, the term “tpx” refers to anything whatsoever, regardless of whether it exists or has any other specific characteristics, about which anything whatsoever may be asserted by any means whatsoever. A ‘tpx’ corresponds exactly to the term ‘resource’ in RDF (defined in RFC 2396 as “anything that has identity”). The address of a tpx that happens to be an information resource is called a subject address.

The Topic Map Standard's (TNMS) subject is a tpx in the sense used here.

Concept→Ttx→Represented by Cnxpt: As used herein, the term “ttx” refers to a cognitive unit of meaning. It is an abstract idea of something formed by combining a set of characteristics. Ttxs are perceived regularities in events or objects, usually designated by a label in a language. Ttxs are also thought of as categories. As categories, they may hold sub-categories. Each ttx may additionally be described by its relationships to other ttxs in a categorization or classification structure, and by its characteristics. Each ttx may be additionally described by (including, but not limited to): name variants, descriptive information, description variants, relationships to other ttxs in a knowledge domain (e.g. in a classification hierarchy), purlieus, cncpttrrts, scopxs, information resources, and attribute values. Ttxs need not be fully described or given names during their infancy. Identity indicators apply to ttxs. In one embodiment, strong limits are placed on what may be defined as being a ttx to reduce the burdens caused by over generality. The term “ttx” refers to a semantic device similar to the ‘subject’ in the Topic Map Standard.

Ttx categorization: As used herein, the term “ttx categorization” refers to a division of the ttxs into classes or groups according to at least one of a particular algorithm to describe an organization of the ttxs in the CMMDB.

Txo Characteristics: As used herein, the term “txo characteristic” or “tpx characteristic” refers to an expansive set of assertions tending to describe a tpx assigned a txo representing the tpx.

Trait Info-item→Trxrt: As used herein, the term “Trxrt” refers to a type of stored knowledge info-item that may be instantiated in the CMMDB and represent cncpttrrts. Trxrts are specializations of txos and represent cncpttrrts.

Trait→Cncpttrrt→Represented by Trxrt: As used herein, the term “trait” or “Cncpttrrt” refers to an assertion regarding a ttx, including, but not limited to: discrete value attributal information or descriptive information. Specializations of cncpttrrts include, but are not limited to: consignment data, features, needs, or requirements.

Topic Info-item→Txxo: As used herein, the term “txxo” refers to a type of knowledge info-item as defined in the ISO's Topic Navigation Map Standard (TNMS) (ISO 13250) and is a symbol used within a topic map to represent one, and only one, subject. A txxo is a machine-processable representation of a unique, clearly identified, and non-ambiguous subject. The set of subjects that can be represented by txxos is not restricted in any way other than needed for civility and legality. Txxos can be used in the CMM to represent tangible things and things that have no tangible form at all, but txxos are not supported by most of the facilities of the CMM, since the “txo” is available.

Txo Info-item: As used herein, the term “txo” refers to a type of stored knowledge info-item, that may be instantiated in the CMMDB, intended to represent one and only one tpx in order to allow statements to be made about the tpx, or a category of other tpxs in order to allow statements to be made about the tpxs in the category in general. Txos share some similarity to txxos, but a txo is not a ‘txxo’ as defined in the TNMS. A txo is a machine-processable object that is intended to represent a non-ambiguous tpx. Some specializations of txos, herein called cnxpts, while merely intended to represent non-ambiguous ttxs, are expected to represent less clearly delineated tpxs for the early portion of their existence. The set of tpxs that a txo may represent is not restricted in any way. Txos can be used to represent tangible things and things that have no tangible form at all.

Txos serve as ‘Infrastructure Concepts’ so that an info-item is available to represent a person, company, product, project, or some other entity not directly addressed or categorized as a cnxpt would be. Specializations of txos also provide for management of infrastructure of the system. To avoid confusion, the mapping between tpx-txo, and ttx-cnxpt are distinguished. To conform with the standards, here we formally use the name txxo where the standard would use the term ‘topic link’ and the name tpx where the standard uses the term ‘subject’.

Cnxpt Info-item→Cnxpt: As used herein, the term “cnxpt” refers to a type of knowledge info-item that represents a ttx. The invisible heart of every cnxpt is the ttx that its author had in mind when it was created. A cnxpt is more a container for an idea or the placeholder for an idea.

Cnxpts also represent ttx categories. Each cnxpt may additionally be described by its relationships to other cnxpts in a categorization or classification structure, and by its infxtypx, scopxs, purlieus, cncpttrrts, characteristics, and attribute values. Cnxpts are restricted specializations of txos, designated by a infxtypx.

In one embodiment, a cnxpt is merely intended to represent a unique, clearly identified, and non-ambiguous ttx. In one embodiment, a cnxpt may represent a less clearly identified, possibly ambiguous ttx.

Technology Concept→Tcept→Represented by Txpt: As used herein, the term “tcept” refers to a cognitive unit of meaning or knowledge perception of at least one of a field of science, a scientific discovery, an industrial design, a business process, a procedure, a tcept category, an innovation, an invention, a utility patent invention, a means, a method, a tcept with an additional or changed feature from another tcept, a generic branding. Tcepts are elements of scientific knowledge or creative ideas for techniques or apparatuses from the human mind.

Technology Cnxpt Info-item→Txpt: Txpt: As used herein, the term “txpt” refers to a cnxpt specifically representing a technology, and thus refers to a type of stored knowledge info-item that may be instantiated in the CMMDB and represents a tcept. Txpts represent perceptions of at least one of a field of science, a tcept category, an innovation, a utility patent invention, a business process, a means, a method, a txpt with an additional or changed feature from another txpt, a generic branding. Each txpt may be named, and may be described by one or more of: a textual description; an abstract; by its relationships to other txpts; purlieus; or by its cncpttrrts (here often referred to as traits, features or requirements), or attribute values.

Application of Technology Concept→Appcept→Represented by Axpt: As used herein, the term “appcept” refers to a cognitive unit of meaning or knowledge perception of at least one of a potential purpose, need, or use for technology, system, or product, probably to help to solve human problems or to create a result or product, or where needs for technologies share relevant commonalities; or a categorization of needs for a technology. It is the problem that someone believes can be solved by a technology.

Application of Technology Cnxpt Info-item→Axpt: As used herein, the term “axpt” refers to a type of stored knowledge info-item that may be instantiated in the CMMDB and represents an appcept that is a purpose, need, or usage for technology or where needs for technologies share relevant commonalities; or a categorization of needs for a technology; or use or potential use of a technology, even if no technology currently exists to support that use. Axpts represent perceptions of, including but not limited to: an application domain, product domain, product line, a generic market, a benefit from technology, a problem that a tcept could solve, a purpose for use of technology, a grouping of requirements that a tcept should address, or a mere bundle of needs.

Overall Description of Invention—Preferred Embodiment: The Use of Textual Input

Third Level for Process: Local or Distributed Processes

Low Level Procedure Models for Use Cases

Procedure—IMPUTE Cnxpts and Associations from Body of Text

Use Case: Procedure—IMPUTE Syntactically Suggested Associations from Body of Text—Create, or concretize into the CMM zero or more new cnxpts, which may or may not have been defined previously, to represent the ttxs described in a body of text, or a document, as transformed into a syntactically suggested association by transformations (generative operations) of the nature of syntax deconstruction or interpretation rules or heuristics. Create, or concretize into the CMM zero or more new associations (infxtypxd binary relationships between cnxpts that represent relationships between the ttxs represented by the cnxpts), where an association may or may not have been defined previously, to represent a relationship between ttxs described in a body of text, or a document as transformed into a syntactically suggested association.

In one embodiment, bodies of text can be used in the process of generating maps. The bodies of text need not be only ‘English’ or other conversational text but in various embodiments could be mathematic, logic, or any other routinized structure of information transfer medium where a set of grammar rule models (small node-edge diagrams showing how language parts can be understood based upon their accepted use in observed phrases in the language) have been developed and a transformation in the form of one or more of a syntax deconstruction or interpretation rule or heuristic to a syntactically suggested association is possible by systematically matching parts of speech and the rule structure that stems from the content of the body of text into a structure that is ‘better minimized’ until the parts of speech are mapped onto a syntactically suggested association with a defined structure.

In one embodiment, bodies of text can be found by “crawling” the World Wide Web, a heterogeneous repository, or document management systems in a methodical, automated manner to analyze data on web pages or in corporate documents and to scrape information for import into the CMMDB. If the result is marked with a fxxt identifier then it can be utilized in map generation when that fxxt identifier is utilized to define the fxxts to be used in a fxxt analysis. Otherwise, the content of the body of text is converted into a structured summary, similar to a mind map, by the operation of the transforms, and imputed into the CMMDB.

A completed syntactically suggested association is: in one embodiment, an association between two ttxs; in one embodiment, an expression of a trait's presence on a single stated ttx; or, in one embodiment, an expression of a typed (an infxtypxd binary relationship) association between two ttxs. In each case, the phrases of the body of text could be broken apart into one or a series of syntactically suggested associations that, due to the expressions made in the body of text and the acceptance of the body of text as being useful by its presentation to be used, that relate information of some veracity that could be used as a basis for the design of a map through the process of analysis of the fxxt defined by the marking of the body of text and the application of syntax deconstruction or interpretation rules or heuristics.

Operation—Information Conversion of Body of Text to Associations During Fxxt Analysis Process Flows

In one embodiment, the information of the body of text would be utilized as a part of the fxxt analysis process when the body is preprocessed sufficiently to be coded as language parts by a natural language processing converter.

In one embodiment, the converter output are phrases marked as language parts with a diagram of the language parts of each phrase as in a transformational or generative grammar. (In one embodiment, for efficiency each phrase will have its parts marked as corresponding to a node in a grammar ‘rule’ of some type for the grammar.)

Because, differently than a simple understanding mechanism for text, the intent to make use of the body of text and its processed components to create a map requires that a fxxt identifier would mark the body of text, and the fxxt identifier would be passed along with the processed components in the process of extracting information from some requested, encompassing set of fxxts that includes the fxxt identifier of the body of text, so that the body of text is used in creating a requested map.

In one embodiment, the phrases would also be associated with strength weights to cause structuring of the end association list by greatest strengths.

The fxxt analysis process would invoke the transformational or generative grammar rules in turn (in one embodiment, by consideration of rules by a type highest in a precedence ordering of rules where the rule can be transformed to make the text content map size smaller) (in one embodiment, by consideration of strongest rule that can be transformed to make the text content map size smaller) (in one embodiment, by consideration of strongest rule of a type highest in a precedence ordering that can be transformed to make the text content map size smaller) to minimize the size of the transformed mapping (of grammar rules associated with specific body of text content) of parts of speech stemming from the body of text.

The prior minimization would terminate when the minimization is achieved. In one embodiment (an example of NOT ‘Easily Determined’ fxxt analysis), minimization would be temporary when other fxxt analysis procedures were being invoked upon the minimization being reached above, which would thus present a larger minimization operation for the fxxt analysis.

Upon minimization, or upon a pre-determined point in NOT ‘Easily Determined’ fxxt analysis where a minimization of the transformed mapping is achieved, or, in one embodiment, where a specific ttx is matched to a substituted part of speech in a syntactically suggested association that is seen as an ‘object’ (In one embodiment, nouns or noun expressions from the original text are defined to be objects for the purpose of this section. In one embodiment, a factor or a result of an equation expressions from the original text are defined to be an object for the purpose of this section.), the cnxpt's identifier of the cnxpt representing the ttx is attached to the part of speech node in the syntactically suggested association. In one embodiment, further minimization might well occur that changes the text or scope of the part of speech node in the syntactically suggested association, requiring a change of (or a nulling of) the cnxpt's identifier of the cnxpt representing the ttx is attached to that node. (In one embodiment, the detection of such a change would generate a second syntactically suggested association to describe an association noticed within the process between the old and the new cnxpts representing the old and the new ttxs attached to that same node.)

Upon minimization, or upon a pre-determined point in NOT ‘Easily Determined’ fxxt analysis where a minimization of the transformed mapping is achieved, but where no ttx is matched to a substituted part of speech in a syntactically suggested association that is seen as an ‘object’ (In one embodiment, nouns or noun expressions from the original text are defined to be objects for the purpose of this section. In one embodiment, a factor or a result of an equation expressions from the original text are defined to be an object for the purpose of this section.), a dummy cnxpt info-item to represent the ttx will be reified and concretized and that cnxpt's identifier will be attached to the part of speech node in the syntactically suggested association. In one embodiment, further minimization might well occur that changes the text or scope of the part of speech node in the syntactically suggested association, requiring a change of (or a nulling of) the cnxpt's identifier of the cnxpt representing the ttx attached to that node. (In one embodiment, the detection of such a change would generate a second syntactically suggested association to describe an association noticed within the process between the old and the new cnxpts representing the old and the new ttxs attached to that same node.)

Upon minimization, or upon a pre-determined point in NOT ‘Easily Determined’ fxxt analysis where a minimization of the transformed mapping is achieved, or, in one embodiment, where a specific ttx is matched to a substituted part of speech in a syntactically suggested association, if the node is the only ‘object’ (In one embodiment, nouns or noun expressions from the original text are defined to be objects for the purpose of this section. In one embodiment, a factor or a result of an equation expressions from the original text are defined to be an object for the purpose of this section.) remaining in the syntactically suggested association, the ttx represented by the cnxpt having the identifier attached to the part of speech node associated with the syntactically suggested association is given a trait, or where there already is a presence of that trait in that cnxpt (representing the ttx), that trait is given an up-tick for its veracity.

Upon minimization, or upon a pre-determined point in NOT ‘Easily Determined’ fxxt analysis where a minimization of the transformed mapping is achieved and all conversions of ‘objects’ (In one embodiment, nouns or noun expressions from the original text are defined to be objects for the purpose of this section. In one embodiment, a factor or a result of an equation expressions from the original text are defined to be an object for the purpose of this section.), for each syntactically suggested association having two ‘objects’ where the connection between the ‘objects’ is of a pre-determined type as defined by the syntactically suggested association, an association relationship info-item between the cnxpts representing the ttxs indicated on the ‘object’ nodes of the syntactically suggested association will be created and marked with the fxxt the text body has been assigned.

Upon minimization, or upon a pre-determined point in NOT ‘Easily Determined’ fxxt analysis where a minimization of the transformed mapping is achieved and all conversions of ‘objects’ (In one embodiment, nouns or noun expressions from the original text are defined to be objects for the purpose of this section. In one embodiment, a factor or a result of an equation expressions from the original text are defined to be an object for the purpose of this section.), for each syntactically suggested association having one or more ‘objects’, and where the ‘object’ is of a pre-determined type as defined by the syntactically suggested association, the cnxpts representing the ttxs indicated on the ‘object’ nodes of the syntactically suggested association will be marked with the fxxt the text body has been assigned. 

What is claimed is:
 1. A computer-implemented method to make available a commonplace of information, comprising: a. providing a computer storage to hold information added to the commonplace of information comprising at least one phrase, a plurality of cnxpts representing concepts, and at least one syntax deconstruction or interpretation rule or heuristic that if applied to an at least one phrase would cause a syntactically suggested association relationship to result between at least two of the plurality of cnxpts representing concepts; b. defining a knowledge model comprising a set of zero or more fxxts based on the information stored regarding the zero or more cnxpts and the at least one syntax deconstruction or interpretation rule or heuristic, fulfilling at least one condition selected from the group of: no association is marked with a fxxt, no cnxpt is marked with a fxxt, at least one cnxpt is marked with at least one fxxt, at least one cnxpt participates in one or more associations marked with at least one fxxt, and the at least one phrase and the at least one syntax deconstruction or interpretation rule or heuristic that if applied to the at least one phrase would cause a syntactically suggested association relationship to result between at least two of the plurality of cnxpts representing concepts; c. generating, using a map definition referencing the set of zero or more fxxts, a derived ontology for one or more domains of wisdom by extracting references to zero or more associations and zero or more cnxpts into the derived ontology; d. generating, using said map definition referencing the set of zero or more fxxts, a skeletal structure for a map instance for said one or more domains of wisdom from the extracted derived ontology; e. generating, using said map definition referencing the set of zero or more fxxts, one or more organizations of knowledge to structure a map instance for said one or more domains of wisdom from the extracted derived ontology wherein the resulting map structure of said map instance is based upon a manner of map assembly selected from the group of: a spanning forest manner, a hierarchical manner, an enhanced descendent forest manner, an enhanced ascendant forest manner, a vertical manner, a directed graph manner, a graph manner, a horizontal manner, a depth augmented manner, a time augmented manner, a purlieu augmented manner, and a structure comprising a combination thereof, wherein vertical and horizontal are mere duals for labeling in combinations; and f. providing to the user said one or more domains of wisdom for utilization; whereby one or more domains of wisdom are formed by collections of references to cnxpts and references to zero or more associations among cnxpts. 